How to Use the Arweave MCP in AutoGen

Q: How do AutoGen agents negotiate Arweave storage costs?

One agent checks the fee using getstorageprice while another checks the budget with getwalletbalance. They converse and only call submittransaction when both agents agree the cost is acceptable.

Run multi-agent debates in AutoGen to verify, price, and submit Arweave transactions autonomously.

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Connect Arweave MCP to AutoGen

Create your Vinkius account to connect Arweave to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Arweave with AutoGen

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Coordinate transaction submission in AutoGen

The `submit_transaction` tool allows your AutoGen agents to post data directly to the permaweb. Before writing to the chain, a writer agent drafts the transaction, while a financial agent checks the cost using `get_storage_price` to confirm it fits the budget. A third auditor agent can check `get_wallet_balance` to ensure the wallet has enough Winstons to cover the upload. The agents negotiate and only execute the submission once they reach a consensus on cost and balance.

Track transaction status with an MCP Server

This MCP Server provides `get_transaction_status` to let your agents monitor confirmation progress. A coordinator agent can assign a background worker agent to repeatedly check the status until the transaction is fully confirmed on the block. If a transaction stalls, a developer agent can call `get_network_info` to check for network congestion. The agents can then debate whether to resubmit the data or wait for the next block, handling network hiccups without human intervention.

Audit permaweb history through agent debate

The `query_graphql` tool lets your agents search historical records to verify compliance or track past uploads. One agent can query the network for specific tags while another runs `get_transaction` to inspect the metadata of the returned results. To verify data integrity, a security agent can fetch the raw payload using `get_transaction_data` and cross-reference it against local hashes. If a discrepancy is found, the agents debate the root cause and log the anomaly automatically.

Setup guide

Set up Arweave MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Arweave tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Arweave_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Arweave data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Arweave_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Arweave data")
    print(result.messages[-1].content)

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Common questions about Arweave MCP in AutoGen

One agent checks the fee using `get_storage_price` while another checks the budget with `get_wallet_balance`. They converse and only call `submit_transaction` when both agents agree the cost is acceptable.

Yes, you can set up a dedicated monitoring agent that polls `get_network_info` and `get_peers`. It can then alert your other agents if peer counts drop or block times slow down.

You import the tool adapter from the AutoGen extension and pass your Vinkius endpoint. This maps all 13 tools, including `get_block_by_height`, to the agent's capabilities automatically.

Yes, AutoGen handles asynchronous tool calls natively. Your agents can query `get_transaction_data` and `query_graphql` in parallel, speeding up multi-agent analysis pipelines.

Yes, they are completely secure. Vinkius executes all queries to `query_graphql` and `get_transaction` in an isolated V8 sandbox. No query history or network logs are retained, keeping your agent's search patterns completely private.

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